A Mid-level Visual Concept Generation Framework for Sports Analysis

The development of mid-level concepts helps to bridge the gap between low-level feature and high-level semantics in video analysis. Most existing work combines the customized mid-level concepts and statistical models to detect particular events. Based on broadcast sports video production knowledge, we extend our previous work to present a unified framework for mid-level concept generation in this paper. A video segment is characterized via three essential aspects: camera shot size, an object appearing in a scene, and video production technology. These three aspects clearly summarize the primary concerns in terms of a generic concept generation. Within this framework, we can flexibly and clearly define meaningful mid-level concepts towards comprehensive video content analysis, such as replay classification and the detection of events (e.g. goal, shoot, attack, foul, offside, and out of bound, etc.)